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Assessment of practices and attitudes of undergraduate students toward family violence in the University of Baghdad
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Objectives: The aim of this study was to assess undergraduate student's practices and attitudes toward family violence in the University of Baghdad.

Methods: This was a descriptive study on non-probability (purposive) sample of 100 undergraduate students from different colleges at the University of Baghdad from November 15, 2022 to May 20, 2023. A validated questionnaire was prepared with 43 questions, which consisted of three parts: eight items related to students’ demographic data, 13 items related to students’ attitudes, and 22 items related to students’ practices.

Results: Positive attitudes toward family violence were used by the parents, and with respect to the total relative sufficiency (86.18%), the attitude level was moderate. Undergraduate students reported low levels of family violence practices from their parents with respect to the total mean scores (1.43) and the relative sufficiency (47.5). There was a significant relationship between students’ practices and their parents’ perception of family violence (p < 0.05).

Conclusion: This study concludes that students in the University of Baghdad had positive, moderate attitudes toward parents’ violence. They also experienced a low level of practice toward family violence, as well as parents’ level of education has an impact on students’ violence practices.

Recommendations: There is a need to raise community awareness about the consequences of family violence and mistreatment of the family members through mass media, and to establish family violence counseling centers for students.

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Fri Jul 01 2016
Journal Name
Composite Structures
Bond behaviour between CFRP laminates and steel members under different loading rates
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Carbon fibre reinforced polymers are widely used to strengthen steel structural elements. These structural elements are normally subjected to static, dynamic and fatigue loadings during their life-time. A number of studies have focused on the characteristics of CFRP sheets bonded to steel members under static, dynamic and fatigue loadings. However, there is a gap in understanding the bonding behaviour between CFRP laminates and steel members under impact loading. This paper shows the effect of different load rates from quasi-static to 300 × 103 mm/min on this bond. Two types of CFRP laminate, CFK 150/2000 and CFK 200/2000, were used to strengthen steel joints using Araldite 420 epoxy. The results show a significant bond strength enhancemen

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Publication Date
Tue Feb 06 2018
Journal Name
International Journal Of Gynecology And Obstetrics
FIGO consensus guidelines on placenta accreta spectrum disorders: Prenatal diagnosis and screening
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Recent population studies have shown that placenta accreta spectrum (PAS) disorders remain undiagnosed before delivery in half to two-thirds of cases. In a series from specialist diagnostic units in the USA, around one-third of cases of PAS disorders were not diagnosed during pregnancy. Maternal

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Publication Date
Sun Jun 01 2025
Journal Name
Methodsx
How mathematical models might predict desertification from global warming and dust pollutants
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine
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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Fog Computing Resource Optimization: A Review on Current Scenarios and Resource Management
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            The unpredictable and huge data generation nowadays by smart computing devices like (Sensors, Actuators, Wi-Fi routers), to handle and maintain their computational processing power in real time environment by centralized cloud platform is difficult because of its limitations, issues and challenges, to overcome these, Cisco introduced the Fog computing paradigm as an alternative for cloud-based computing. This recent IT trend is taking the computing experience to the next level. It is an extended and advantageous extension of the centralized cloud computing technology. In this article, we tried to highlight the various issues that currently cloud computing is facing. Here

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Wed Jan 01 2025
Journal Name
Iraqi Journal Of Materials
Silicon Nitride Nanostructures Prepared from n-type and p-type Silicon Targets
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Silicon nitride nanostructures were prepared by reactive sputtering technique using silicon targets with different types of electrical conductivity (n-type and p-type) and Ar:N2 gas mixing ratio of 70:30. The optical microscopy and spectroscopic characteristics of these films were determined in order to introduce the effect of target conductivity type on these characteristics. The results showed that using p-type silicon target would produce Si3N4 films with lower tendency to adsorb water vapor and other constituents of the atmospheric air, higher absorbance in the visible range 400-700nm, and lower variation in the energy band gap with film thickness than the Si3N4 films prepared from n-type silicon target.

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Assessing Service Quality using Data Envelopment analysis Case study at the Iraqi Middle East Investment Bank
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The use of data envelopment analysis method helps to improve the performance of organizations in order to exploit their resources efficiently in order to improve the service quality. represented study a problem in need of the Iraqi Middle East Investment Bank to assess the performance of bank branches, according to the service quality provided, Thus, the importance of the study is to contribute using a scientific and systematic method by applying  the data envelopment analysis method in assessing the service quality provided by the bank branches, The study focused on achieving the goal of determining the efficiency of the  services quality provided by the bank branches manner which reflect the extent of utilization of a

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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Creating a LabVIEW Sub VI for the INA219 Sensor for Detecting Extremely Low-Level Electrical Quantities
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An impressed current cathodic protection system (ICCP) requires measurements of extremely low-level quantities of its electrical characteristics. The current experimental work utilized the Adafruit INA219 sensor module for acquiring the values for voltage, current, and power of a default load, which consumes quite low power and simulates an ICCP system. The main problem is the adaptation of the INA219 sensor to the LabVIEW environment due to the absence of the library of this sensor. This work is devoted to the adaptation of the Adafruit INA219 sensor module in the LabVIEW environment through creating, developing, and successfully testing a Sub VI to be ready for employment in an ICCP system. The sensor output was monitored with an Ardui

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